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A comparative survey of integrated learning systems
This paper presents the duction framework for unifying the three basic forms of inference - deduction, abduction, and induction - by specifying the possible relationships and influences among them in the context of integrated learning. Special assumptive forms of inference are defined that extend the use of these inference methods, and the properties of these forms are explored. A comparison to a related inference-based learning frame work is made. Finally several existing integrated learning programs are examined in the perspective of the duction framework
Review of Jon and Susan Josephson, “Abductive Inference”
This article reviews the book '“Abductive Inference” by Jon and Susan Josephson
A comparison of techniques for learning and using mathematics and a study of their relationship to logical principles
Various techniques exist for learning mathematical concepts, like experimentation and exploration, respectively using mathematics, like modelling and simulation. For a clear application of such techniques in mathematics education, there should be a clear distinction between these techniques.
A recently developed theory of fuzzy concepts can be applied to analyse the four mentioned concepts. For all four techniques one can pose the question of their relationship to deduction, induction and abduction as logical principles. An empirical study was conducted with 12-13 aged students, aiming at checking the three reasoning processes
A New Rational Algorithm for View Updating in Relational Databases
The dynamics of belief and knowledge is one of the major components of any
autonomous system that should be able to incorporate new pieces of information.
In order to apply the rationality result of belief dynamics theory to various
practical problems, it should be generalized in two respects: first it should
allow a certain part of belief to be declared as immutable; and second, the
belief state need not be deductively closed. Such a generalization of belief
dynamics, referred to as base dynamics, is presented in this paper, along with
the concept of a generalized revision algorithm for knowledge bases (Horn or
Horn logic with stratified negation). We show that knowledge base dynamics has
an interesting connection with kernel change via hitting set and abduction. In
this paper, we show how techniques from disjunctive logic programming can be
used for efficient (deductive) database updates. The key idea is to transform
the given database together with the update request into a disjunctive
(datalog) logic program and apply disjunctive techniques (such as minimal model
reasoning) to solve the original update problem. The approach extends and
integrates standard techniques for efficient query answering and integrity
checking. The generation of a hitting set is carried out through a hyper
tableaux calculus and magic set that is focused on the goal of minimality.Comment: arXiv admin note: substantial text overlap with arXiv:1301.515
Compilability of Abduction
Abduction is one of the most important forms of reasoning; it has been
successfully applied to several practical problems such as diagnosis. In this
paper we investigate whether the computational complexity of abduction can be
reduced by an appropriate use of preprocessing. This is motivated by the fact
that part of the data of the problem (namely, the set of all possible
assumptions and the theory relating assumptions and manifestations) are often
known before the rest of the problem. In this paper, we show some complexity
results about abduction when compilation is allowed
Using temporal abduction for biosignal interpretation: A case study on QRS detection
In this work, we propose an abductive framework for biosignal interpretation,
based on the concept of Temporal Abstraction Patterns. A temporal abstraction
pattern defines an abstraction relation between an observation hypothesis and a
set of observations constituting its evidence support. New observations are
generated abductively from any subset of the evidence of a pattern, building an
abstraction hierarchy of observations in which higher levels contain those
observations with greater interpretative value of the physiological processes
underlying a given signal. Non-monotonic reasoning techniques have been applied
to this model in order to find the best interpretation of a set of initial
observations, permitting even to correct these observations by removing, adding
or modifying them in order to make them consistent with the available domain
knowledge. Some preliminary experiments have been conducted to apply this
framework to a well known and bounded problem: the QRS detection on ECG
signals. The objective is not to provide a new better QRS detector, but to test
the validity of an abductive paradigm. These experiments show that a knowledge
base comprising just a few very simple rhythm abstraction patterns can enhance
the results of a state of the art algorithm by significantly improving its
detection F1-score, besides proving the ability of the abductive framework to
correct both sensitivity and specificity failures.Comment: 7 pages, Healthcare Informatics (ICHI), 2014 IEEE International
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